Resolving versions in an append-only large-scale data store in distributed data management systems

ABSTRACT

One embodiment provides for a method including performing, by a processing thread, a process that analyzes transactional operations by maintaining the transactional operations in transaction local side logs, and waiting until a successful transaction commit to append the transaction local side logs to a log stream. The processing thread processes the transactional operations on a key used to determine whether existing data is found for the key. The transactional operations are sped up through parallelism based on partitioning tables across nodes handling the transactional operations. A first process is performed by a first processor that processes updates for values of a key based on updating a first start time table index using unique keys and a start time field of a row for a first appearance of each unique key from the transactional operations.

BACKGROUND

Conventional data management systems that target high-availability haveto allow transactional operations, such as updates, deletes, and inserts(UDIs) to go to any replica of data. The transactional operations alsotarget compatibility with the big data ecosystem, which uses append-only(and hence mutation unfriendly) storage streams because of theirsuperiority in efficient read and write operations and spaceconsumption. Updates are traditionally a problem for versioneddatabases. Consider an update to a record inserted five years back. Theoriginal version of that record is likely migrated to a read-friendlystorage system (such as an object store), which is not efficient atrandom access, and may not support any in-place updates.

SUMMARY

Embodiments relate to processing updates for key values and speed up ofprocessing for patch up of prior versions of updates and not yet patchedupdates. One embodiment provides for a method including performing, by aprocessing thread, a process that analyzes transactional operations bymaintaining the transactional operations in transaction local side logs,and waiting until a successful transaction commit to append thetransaction local side logs to a log stream. The processing threadprocesses the transactional operations on a key used to determinewhether existing data is found for the key. The transactional operationsare sped up through parallelism based on partitioning tables acrossnodes handling the transactional operations. A first process isperformed by a first processor that processes updates for values of akey based on updating a first start time table index using unique keysand a start time field of a row for a first appearance of each uniquekey from the transactional operations.

These and other features, aspects and advantages of the presentinvention will become understood with reference to the followingdescription, appended claims and accompanying figures.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 depicts a cloud computing environment, according to anembodiment;

FIG. 2 depicts a set of abstraction model layers, according to anembodiment;

FIG. 3 is a network architecture for a multi-master distributed datamanagement system, according to an embodiment;

FIG. 4 shows a representative hardware environment that may beassociated with the servers and/or clients of FIG. 1, according to anembodiment;

FIG. 5 is a block diagram illustrating a multi-master distributed datamanagement system for performing processing updates for key values andfor patch up of prior versions of updates and not yet patched updates,according to one embodiment;

FIG. 6 illustrates an example architecture for performing a groomingprocess in a multi-master distributed data management system, accordingto one embodiment;

FIG. 7 illustrates a life cycle example for data in a multi-masterdistributed data management system, according to one embodiment;

FIG. 8 illustrates an example of grooming data in a multi-masterdistributed data management system, according to one embodiment;

FIG. 9 illustrates an example block diagram for a rollup process forprocessing updates for key values and for patch up of prior versions ofupdates and not yet patched updates, according to one embodiment; and

FIG. 10 illustrates a block diagram for a process for performingprocessing updates for key values and for patch up of prior versions ofupdates and not yet patched updates, according to one embodiment.

DETAILED DESCRIPTION

The descriptions of the various embodiments have been presented forpurposes of illustration, but are not intended to be exhaustive orlimited to the embodiments disclosed. Many modifications and variationswill be apparent to those of ordinary skill in the art without departingfrom the scope and spirit of the described embodiments. The terminologyused herein was chosen to best explain the principles of theembodiments, the practical application or technical improvement overtechnologies found in the marketplace, or to enable others of ordinaryskill in the art to understand the embodiments disclosed herein.

It is understood in advance that although this disclosure includes adetailed description of cloud computing, implementation of the teachingsrecited herein are not limited to a cloud computing environment. Rather,embodiments of the present invention are capable of being implemented inconjunction with any other type of computing environment now known orlater developed.

Embodiments relate to transactional operations (e.g., updates, deletes,inserts, etc.) in multi-master distributed data management systems. Oneembodiment provides a method including processing transactionaloperations on a key used to determine whether existing data is found forthat key. A first time index is updated using unique keys and a starttime field of a first appearance of each key from the transactionaloperations. A deferred update of prior versions of the key is performedfor non-recent data upon determining that recent data in thetransactional operations is found for the key.

Cloud computing is a model of service delivery for enabling convenient,on-demand network access to a shared pool of configurable computingresources (e.g., networks, network bandwidth, servers, processing,memory, storage, applications, virtual machines (VMs), and services)that can be rapidly provisioned and released with minimal managementeffort or interaction with a provider of the service. This cloud modelmay include at least five characteristics, at least three servicemodels, and at least four deployment models.

Characteristics are as follows:

On-demand self-service: a cloud consumer can unilaterally provisioncomputing capabilities, such as server time and network storage, asneeded and automatically, without requiring human interaction with theservice's provider.

Broad network access: capabilities are available over a network andaccessed through standard mechanisms that promote use by heterogeneous,thin or thick client platforms (e.g., mobile phones, laptops, and PDAs).

Resource pooling: the provider's computing resources are pooled to servemultiple consumers using a multi-tenant model, with different physicaland virtual resources dynamically assigned and reassigned according todemand. There is a sense of location independence in that the consumergenerally has no control or knowledge over the exact location of theprovided resources but may be able to specify location at a higher levelof abstraction (e.g., country, state, or data center).

Rapid elasticity: capabilities can be rapidly and elasticallyprovisioned and, in some cases, automatically, to quickly scale out andrapidly released to quickly scale in. To the consumer, the capabilitiesavailable for provisioning often appear to be unlimited and can bepurchased in any quantity at any time.

Measured service: cloud systems automatically control and optimizeresource use by leveraging a metering capability at some level ofabstraction appropriate to the type of service (e.g., storage,processing, bandwidth, and active consumer accounts). Resource usage canbe monitored, controlled, and reported, thereby providing transparencyfor both the provider and consumer of the utilized service.

Service Models are as follows:

Software as a Service (SaaS): the capability provided to the consumer isthe ability to use the provider's applications running on a cloudinfrastructure. The applications are accessible from various clientdevices through a thin client interface, such as a web browser (e.g.,web-based email). The consumer does not manage or control the underlyingcloud infrastructure including network, servers, operating systems,storage, or even individual application capabilities, with the possibleexception of limited consumer-specific application configurationsettings.

Platform as a Service (PaaS): the capability provided to the consumer isthe ability to deploy onto the cloud infrastructure consumer-created oracquired applications created using programming languages and toolssupported by the provider. The consumer does not manage or control theunderlying cloud infrastructure including networks, servers, operatingsystems, or storage, but has control over the deployed applications andpossibly application-hosting environment configurations.

Infrastructure as a Service (IaaS): the capability provided to theconsumer is the ability to provision processing, storage, networks, andother fundamental computing resources where the consumer is able todeploy and run arbitrary software, which can include operating systemsand applications. The consumer does not manage or control the underlyingcloud infrastructure but has control over operating systems, storage,deployed applications, and possibly limited control of select networkingcomponents (e.g., host firewalls).

Deployment Models are as follows:

Private cloud: the cloud infrastructure is operated solely for anorganization. It may be managed by the organization or a third party andmay exist on-premises or off-premises.

Community cloud: the cloud infrastructure is shared by severalorganizations and supports a specific community that has shared concerns(e.g., mission, security requirements, policy, and complianceconsiderations). It may be managed by the organizations or a third partyand may exist on-premises or off-premises.

Public cloud: the cloud infrastructure is made available to the generalpublic or a large industry group and is owned by an organization sellingcloud services.

Hybrid cloud: the cloud infrastructure is a composition of two or moreclouds (private, community, or public) that remain unique entities butare bound together by standardized or proprietary technology thatenables data and application portability (e.g., cloud bursting for loadbalancing between clouds).

A cloud computing environment is a service oriented with a focus onstatelessness, low coupling, modularity, and semantic interoperability.At the heart of cloud computing is an infrastructure comprising anetwork of interconnected nodes.

Referring now to FIG. 1, an illustrative cloud computing environment 50is depicted. As shown, cloud computing environment 50 comprises one ormore cloud computing nodes 10 with which local computing devices used bycloud consumers, such as, for example, personal digital assistant (PDA)or cellular telephone 54A, desktop computer 54B, laptop computer 54C,and/or automobile computer system 54N may communicate. Nodes 10 maycommunicate with one another. They may be grouped (not shown) physicallyor virtually, in one or more networks, such as private, community,public, or hybrid clouds as described hereinabove, or a combinationthereof. This allows the cloud computing environment 50 to offerinfrastructure, platforms, and/or software as services for which a cloudconsumer does not need to maintain resources on a local computingdevice. It is understood that the types of computing devices 54A-N shownin FIG. 2 are intended to be illustrative only and that computing nodes10 and cloud computing environment 50 can communicate with any type ofcomputerized device over any type of network and/or network addressableconnection (e.g., using a web browser).

Referring now to FIG. 2, a set of functional abstraction layers providedby the cloud computing environment 50 (FIG. 1) is shown. It should beunderstood in advance that the components, layers, and functions shownin FIG. 2 are intended to be illustrative only and embodiments of theinvention are not limited thereto. As depicted, the following layers andcorresponding functions are provided:

Hardware and software layer 60 includes hardware and softwarecomponents. Examples of hardware components include: mainframes 61; RISC(Reduced Instruction Set Computer) architecture based servers 62;servers 63; blade servers 64; storage devices 65; and networks andnetworking components 66. In some embodiments, software componentsinclude network application server software 67 and database software 68.

Virtualization layer 70 provides an abstraction layer from which thefollowing examples of virtual entities may be provided: virtual servers71; virtual storage 72; virtual networks 73, including virtual privatenetworks; virtual applications and operating systems 74; and virtualclients 75.

In one example, a management layer 80 may provide the functionsdescribed below. Resource provisioning 81 provides dynamic procurementof computing resources and other resources that are utilized to performtasks within the cloud computing environment. Metering and pricing 82provide cost tracking as resources are utilized within the cloudcomputing environment and billing or invoicing for consumption of theseresources. In one example, these resources may comprise applicationsoftware licenses. Security provides identity verification for cloudconsumers and tasks as well as protection for data and other resources.User portal 83 provides access to the cloud computing environment forconsumers and system administrators. Service level management 84provides cloud computing resource allocation and management such thatrequired service levels are met. Service Level Agreement (SLA) planningand fulfillment 85 provide pre-arrangement for, and procurement of,cloud computing resources for which a future requirement is anticipatedin accordance with an SLA.

Workloads layer 90 provides examples of functionality for which thecloud computing environment may be utilized. Examples of workloads andfunctions which may be provided from this layer include: mapping andnavigation 91; software development and lifecycle management 92; virtualclassroom education delivery 93; data analytics processing 94;transaction processing 95; and updates for key values and for patch upof prior versions of updates and not yet patched updates processing 96.As mentioned above, all of the foregoing examples described with respectto FIG. 2 are illustrative only, and the invention is not limited tothese examples.

It is understood all functions of one or more embodiments as describedherein may be typically performed by the processing system 300 (FIG. 3)or the cloud environment 410 (FIG. 4), which can be tangibly embodied ashardware processors and with modules of program code. However, this neednot be the case for non-real-time processing. Rather, for non-real-timeprocessing the functionality recited herein could be carriedout/implemented and/or enabled by any of the layers 60, 70, 80 and 90shown in FIG. 2.

It is reiterated that although this disclosure includes a detaileddescription on cloud computing, implementation of the teachings recitedherein are not limited to a cloud computing environment. Rather, theembodiments of the present invention may be implemented with any type ofclustered computing environment now known or later developed.

FIG. 3 illustrates a network architecture 300, in accordance with oneembodiment. As shown in FIG. 3, a plurality of remote networks 302 areprovided, including a first remote network 304 and a second remotenetwork 306. A gateway 301 may be coupled between the remote networks302 and a proximate network 308. In the context of the present networkarchitecture 300, the networks 304, 306 may each take any formincluding, but not limited to, a LAN, a WAN, such as the Internet,public switched telephone network (PSTN), internal telephone network,etc.

In use, the gateway 301 serves as an entrance point from the remotenetworks 302 to the proximate network 308. As such, the gateway 301 mayfunction as a router, which is capable of directing a given packet ofdata that arrives at the gateway 301, and a switch, which furnishes theactual path in and out of the gateway 301 for a given packet.

Further included is at least one data server 314 coupled to theproximate network 308, which is accessible from the remote networks 302via the gateway 301. It should be noted that the data server(s) 314 mayinclude any type of computing device/groupware. Coupled to each dataserver 314 is a plurality of user devices 316. Such user devices 316 mayinclude a desktop computer, laptop computer, handheld computer, printer,and/or any other type of logic-containing device. It should be notedthat a user device 311 may also be directly coupled to any of thenetworks in some embodiments.

A peripheral 320 or series of peripherals 320, e.g., facsimile machines,printers, scanners, hard disk drives, networked and/or local storageunits or systems, etc., may be coupled to one or more of the networks304, 306, 308. It should be noted that databases and/or additionalcomponents may be utilized with, or integrated into, any type of networkelement coupled to the networks 304, 306, 308. In the context of thepresent description, a network element may refer to any component of anetwork.

According to some approaches, methods and systems described herein maybe implemented with and/or on virtual systems and/or systems, whichemulate one or more other systems, such as a UNIX system that emulatesan IBM z/OS environment, a UNIX system that virtually hosts a MICROSOFTWINDOWS environment, a MICROSOFT WINDOWS system that emulates an IBMz/OS environment, etc. This virtualization and/or emulation may beimplemented through the use of VMWARE software in some embodiments.

FIG. 4 shows a representative hardware system 400 environment associatedwith a user device 316 and/or server 314 of FIG. 3, in accordance withone embodiment. In one example, a hardware configuration includes aworkstation having a central processing unit 410, such as amicroprocessor, and a number of other units interconnected via a systembus 412. The workstation shown in FIG. 4 may include a Random AccessMemory (RAM) 414, Read Only Memory (ROM) 416, an I/O adapter 418 forconnecting peripheral devices, such as disk storage units 420 to the bus412, a user interface adapter 422 for connecting a keyboard 424, a mouse426, a speaker 428, a microphone 432, and/or other user interfacedevices, such as a touch screen, a digital camera (not shown), etc., tothe bus 412, communication adapter 434 for connecting the workstation toa communication network 435 (e.g., a data processing network) and adisplay adapter 436 for connecting the bus 412 to a display device 438.

In one example, the workstation may have resident thereon an operatingsystem, such as the MICROSOFT WINDOWS Operating System (OS), a MAC OS, aUNIX OS, etc. In one embodiment, the system 400 employs a POSIX® basedfile system. It will be appreciated that other examples may also beimplemented on platforms and operating systems other than thosementioned. Such other examples may include operating systems writtenusing JAVA, XML, C, and/or C++ language, or other programming languages,along with an object oriented programming methodology. Object orientedprogramming (OOP), which has become increasingly used to develop complexapplications, may also be used.

FIG. 5 is a block diagram illustrating a system 500 that may be employedfor performing processing updates for key values and for patch up ofprior versions of updates and not yet patched updates, according to oneembodiment. In one embodiment, the system 500 includes client devices510 (e.g., mobile devices, smart devices, computing systems, etc.), acloud or resource sharing environment 520 (e.g., a public cloudcomputing environment, a private cloud computing environment, adatacenter, etc.), and servers 530. In one embodiment, the clientdevices are provided with cloud services from the servers 530 throughthe cloud or resource sharing environment 520.

In one embodiment, system 500, a periodic background process referred toas grooming, analyzes transactional operations (e.g., updates, deletes,inserts (UDIs)) from multi-statement transactions executed on amulti-master system, and publishes the UDIs on an append-only storagestream. In one embodiment, for the grooming process the multi-mastersystem maintains/keeps the UDIs of ongoing multi-statement transactionsin a transaction-local side-log. Only upon a successful transactioncommit, the transaction-local side-logs are appended to the log stream.The grooming process only reads the log stream, therefore, the groomingprocess avoids being aware of uncommitted transaction changes. Thethread performing the grooming process (also referred to as “groomer”)provides a cursor or indication on the log stream to remember where itleft off in the previous grooming cycle. The log stream that is prior towhere the groomer's cursor or indication points to is marked fordeletion.

In one embodiment, rollup processing periodically moves groomed datafrom a groomed zone (e.g., groomed zone 711, FIGS. 7, 9) to an optimizedzone (optimized zone 901, FIG. 9) separating groomed blocks 855 (FIGS.8, 9) current from history. Small groomed blocks are merged into largeblocks 855. Data is partitioned based on the partition key. Rollupprocessing supports updates (mark and move previous value of a key intohistory), and time travel (allows querying old values of a key). In oneembodiment, the rollup processing handles conflict resolution(concurrent updates to the same data item) in a data store (e.g., adatabase or a key-value store) setting.

In one embodiment, versions in an append-only large-scale data store areefficiently resolved based on a first procedure including an updateprocessor that processes updates for the values of a key, and a secondprocedure including a rollup processor that patches up prior versions.Inserts for new keys are handled as updates that specify values for thefirst version of that key. Deletes of keys are handled as updates thatchange the value of a key to an indicator indicating that it is deleted.

FIG. 6 illustrates an example architecture 600 for performing groomingprocesses and rollup processes in a multi-master distributed datamanagement system, according to one embodiment. In one embodiment, thearchitecture 600 includes applications 610, task coordinators 620,execution engines 630, for analytical nodes 650, execution engines 640for transactional nodes 655 and storage 660. In one embodiment, theapplications 610 may include analytics applications 611 that tolerateslightly stale data and requires most recent data, and high volumetransaction applications 612. In one embodiment, the analytical nodes650 only handle read-only operations. The transactional nodes 655 areresponsible for grooming transaction operations (e.g., UDIs) andperforming rollup processes. The execution engines 640 include multipleexecution engines 645 connected with memory devices 646 (e.g., solidstate drive(s) (SSD)) and non-volatile memory (NVM), such as read-onlymemory, flash memory, ferroelectric RAM, magnetic computer storagedevices (e.g., hard disk drives, floppy disks, and magnetic tape,optical discs, etc.). The storage 660 may include a shared file system,object store, or both.

In one embodiment, to speed up UDI operations through parallelism, thetables in the multi-master system that includes the architecture 600 arepartitioned across nodes handling transactions based upon a subset of aprimary (single-column or composite) key. A table shard is also assignedto (a configurable number of) multiple nodes (transactional nodes 655)for higher availability. In addition to the transactional nodes 655 thatare responsible from UDI operations and lookups on data, the analyticalnodes 650 are only responsible for analytical read requests. Adistributed coordination system includes the task coordinators 620 thatmanage the meta-information related to replication, and a catalogmaintains the schema information for each table. One or more embodimentsalso allow external readers to read data ingested via the multi-mastersystem without involving the local system components, but those readerswill be unable to see the latest transactional data stored on thetransactional nodes 655 handling UDI operations.

In one embodiment, each transaction handled by the architecture 600maintains its un-committed changes in a transaction-local side-log 811(FIG. 8) composed of one or more log blocks. Each log block may containtransactions for only one table. At commit time, the transaction appendsits transaction-local side-log 811 to the log 812 (FIG. 8), which iskept both in storage 660 (memory 810, FIG. 8) and persisted on disk(SSD/NVM 646 (830, FIG. 8)). Additionally, the transaction-localside-log 811 is copied to each of the other transactional nodes 655 thatare responsible for maintaining a replica of that shard's data, foravailability. While any replica of a shard may process any transactionalrequest for that shard (multi-master), one of the replicas periodicallyinvokes a grooming operation or process. This grooming operation scansthe log 812 and groups together the log blocks from multiple (committed)transactions for the same table, creating larger groomed blockscontaining data only from a single table (see, e.g., FIG. 8, groomeddata 855).

FIG. 7 illustrates a life cycle example 700 for data in a multi-masterdistributed data management system including architecture 600 (FIG. 6),according to one embodiment. In one embodiment, the life of data isrepresented by recent data 701 and old data 702. The recent data 701belongs to the live zone (latest) 710 whereas the old data belongs tothe groomed zone 711 (e.g., ˜1 second stale). The transactional nodes655 belong to the live zone 710, and receive inserts, updates and deletetransactional operations 720 and read-only operations 721 that need thelatest data. The analytical nodes 650 belong to the groomed zone 711 andreceive input 730 including: point lookups 731, business intelligentoperations 732, and machine learning (read-only) operations 733. Asillustrated, the data in the live zone 710 moves over to the groomedzone 711 as it becomes older data.

FIG. 8 illustrates an example 800 of grooming data in a multi-masterdistributed data management system, according to one embodiment. Asillustrated, the un-committed changes are recorded/stored in atransaction-local side-log 811 composed of one or more log blocks. Thelog record 815 of a table includes the log blocks for the log(persistent) 812. The transaction appends its transaction-local side-log811 to the log 812, which is kept both in memory 810 and persisted ondisk SSD/NVM 830. In the SSD/NVM 830, the log 812 is processed inrecords 835 and cached as cached data 840. The groomed data 855 thatresults from the grooming process is stored in the shared filesystem/object store 850 (or storage 660, FIG. 6).

FIG. 9 illustrates an example block diagram 900 for a rollup process,according to one embodiment. In the high-level example block diagram900, the process includes input of groomed blocks 855 from thepersistent log 812, which are moved from the groomed zone 711 to theoptimized zone 901 as follows. The groomer does not handle updates,therefore, the same key may appear multiple times in the groomed data ofthe groomed blocks 855. Herein, the latest row is the latest row for akey, and a retired row is a row that is not the latest row for a key.

In one embodiment, the first portion of the process is moving thegroomed blocks 855 to the optimized zone 901 where the latest rows ingroomed zone 711 are moved to the current portion of the optimized zone901 shown by the dashed lines 910 going to the partitions 920. Theretired rows in the groomed zone 711 are moved to the historic portionof the optimized zone 901 shown by the dashed lines 915 going to thepartitions 925. For the second portion of the process, thecurrent=>History within optimized zone 901 as follows. The processingmarks the retired rows in the previous current by using a bit map. Theretired rows in the previous current (retired by latest groomed rows)are moved to the history portion shown by the arrows 930. Furtherdetails of the first portion and the second portion of processing aredescribed below.

In one embodiment, processing detects the recently groomed files. Thedetected groomed data (groomed blocks 855) are moved into the optimizedzone 901 as described below. The output of this portion of processingare: an index referred to as FirstKnownStartTimeIndex, which maps a keyto a beginTime field of a row for the first appearance of the key; acurrent file per partition key; and a history file per partition key.Next, all the affected current files are found by querying an index withthe keys in the FirstKnownStartTimeIndex. The affected files contain atleast one row that is retired by the new groomed rows. Next, processingretires rows from affected current files and outputs a history file perpartition key and a new bit map for each affected file which marks downthe retired rows.

In one embodiment, the first processing portion of moving the groomedblocks 855 data into the optimized zone 901 includes the following. Theprocessing initializes a global in-memory index, referred to asFirstKnownStartTimeIndex. The detected groomed files are scanned inparallel and all rows are grouped by a partition key. For each partitionkey group: a current file and a history file are created for thispartition key. All rows in this group are grouped by primary key. Foreach primary key group: processing sorts rows by value in a BeginTimefield of a row; put (key, BeginTime) of the first row into theFirstKnownStartTimeIndex; For all rows but the last: processing assignsEndTime: row_(i).EndTime=row_(i+1).BeginTime, and this row is written tothe history file; Write the last row to the current file; the currentfile and the history file are closed. The bit map index of the currentfile is initialized (e.g., so that it contains all l's).

In one embodiment, the second processing portion of retiring rows fromcurrent files includes the following. The affected current files aregrouped based on the partition key and the groups are then scanned inparallel. For each partition key group: processing creates a historyfile for this partition key. For each current file in this group:processing creates a new bit map index by copying the previous versionof the bit map index. Processing then loops through each row andperforms processing including: if the key of the row is in theFirstKnownStartTimeIndex (this row is retired) then assign the EndTimerow field as follows: row.EndTime=FirstKnownStartTime(key).BeginTime.The row is then written to the history file. Processing marks the bitmap index to indicate that this row is retired. Then the bit map indexand the history file are each closed.

In one embodiment, fault tolerance of rollup is achieved throughcheckpointing. When a rollup process fails, a new rollup process may bebrought up to resume from a last successful checkpoint. The lastsuccessful rollup sequence number is stored in a fault tolerantcoordinator such as Apache Zookeeper. The last groomed block 855 ID forthis rollup round is needed by the processing engine, but not used forfault tolerance. A checkpoint file with each rollup sequence number isstored on the object store and includes the following: the range ofgroomed block Ids, the last current block ID, the last history block ID,and a snapshot of the list of current files with their latest bit maps.

In one embodiment, snapshot files for queries includes the following.Rollup happens concurrently with queries. There is a need to ensure theconsistency of the query results. After each successful rollup, asnapshot file is published that contains the list of current files withtheir latest bit maps, and a new query is against the files in thesnapshot of the latest successful rollup.

FIG. 10 illustrates a block diagram for process 1000 for performingprocessing updates for key values and for patch up of prior versions ofupdates and not yet patched updates in a system, such as multi-masterdistributed data management system, append-only system, etc., accordingto one embodiment. In one embodiment, in block 1010 process 1000performs processing of transactional operations on a key used todetermine whether existing data is found for that key. In block 1020,process 1000 updates a FirstKnownStartTimeIndex (or first time index)using the unique keys and the BeginTime (or a start time) field of thefirst appearance of each key from the transactional operations. In block1030, process 1000 performs a deferred update of prior versions of thekey for non-recent data upon determining that recent data in thetransactional operations is found for the key. In one embodiment, thetransactional operations comprise update, delete and insert operations.

In one embodiment, process 1000 may include that performing the deferredupdate includes adding a FirstKnownStartTimeIndex using the unique keysand the BeginTime field of the first appearance of each key from thetransactional operations, and performing look ups of theFirstKnownStartTimeIndex for unknown value of the EndTime field of therows in non-recent data. In one embodiment, the EndTime field of a rowin the non-recent data is not assigned upon determining the key is notin the FirstKnownStartTimeIndex.

In one embodiment, in process 1000 the EndTime (or end time) field of arow in the non-rencent data is not assigned upon determining the key isnot in the FirstKnownStartTimeIndex, and bitmap indexes are used to markdeleted rows. Process 1000 may further include that theFirstKnownStartTimeIndex maps a key to a BeginTime field of a row for afirst appearance of the key.

In one embodiment, process 1000 may further include retiring rows fromaffected current files, outputting a history file per partition key, andgenerating a new bit map for each affected file, wherein the new bit mapincludes marking for the retired rows.

In one embodiment, process 1000 may additionally include initializing,the FirstKnownStartTimeIndex, creating a current file and a history filefor each partition key group for a partition key, grouping all rows in apartition key group by primary key, for each primary key group: sortingrows by value in a BeginTime field of a row; writing of a first row intothe FirstKnownStartTimeIndex; and for all rows except for a last rowwriting values to a history file. In one embodiment end time is assignedas row_(i).EndTime=row_(i+1).BeginTime, where i is an integer indicatingthe position of the row in the sorted order of the primary key group,and the last row is written to the current file.

As will be appreciated by one skilled in the art, aspects of the presentinvention may be embodied as a system, method or computer programproduct. Accordingly, aspects of the present invention may take the formof an entirely hardware embodiment, an entirely software embodiment(including firmware, resident software, micro-code, etc.) or anembodiment combining software and hardware aspects that may allgenerally be referred to herein as a “circuit,” “module” or “system.”Furthermore, aspects of the present invention may take the form of acomputer program product embodied in one or more computer readablemedium(s) having computer readable program code embodied thereon.

Any combination of one or more computer readable medium(s) may beutilized. The computer readable medium may be a computer readable signalmedium or a computer readable storage medium. A computer readablestorage medium may be, for example, but not limited to, an electronic,magnetic, optical, electromagnetic, infrared, or semiconductor system,apparatus, or device, or any suitable combination of the foregoing. Morespecific examples (a non-exhaustive list) of the computer readablestorage medium would include the following: an electrical connectionhaving one or more wires, a portable computer diskette, a hard disk, arandom access memory (RAM), a read-only memory (ROM), an erasableprogrammable read-only memory (EPROM or Flash memory), an optical fiber,a portable compact disc read-only memory (CD-ROM), an optical storagedevice, a magnetic storage device, or any suitable combination of theforegoing. In the context of this document, a computer readable storagemedium may be any tangible medium that can contain, or store a programfor use by or in connection with an instruction execution system,apparatus, or device.

A computer readable signal medium may include a propagated data signalwith computer readable program code embodied therein, for example, inbaseband or as part of a carrier wave. Such a propagated signal may takeany of a variety of forms, including, but not limited to,electro-magnetic, optical, or any suitable combination thereof. Acomputer readable signal medium may be any computer readable medium thatis not a computer readable storage medium and that can communicate,propagate, or transport a program for use by or in connection with aninstruction execution system, apparatus, or device.

Program code embodied on a computer readable medium may be transmittedusing any appropriate medium, including but not limited to wireless,wireline, optical fiber cable, RF, etc., or any suitable combination ofthe foregoing.

Computer program code for carrying out operations for aspects of thepresent invention may be written in any combination of one or moreprogramming languages, including an object oriented programming languagesuch as Java, Smalltalk, C++ or the like and conventional proceduralprogramming languages, such as the “C” programming language or similarprogramming languages. The program code may execute entirely on theuser's computer, partly on the user's computer, as a stand-alonesoftware package, partly on the user's computer and partly on a remotecomputer or entirely on the remote computer or server. In the latterscenario, the remote computer may be connected to the user's computerthrough any type of network, including a local area network (LAN) or awide area network (WAN), or the connection may be made to an externalcomputer (for example, through the Internet using an Internet ServiceProvider).

Aspects of the present invention are described below with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems) and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer program instructions. These computer program instructions maybe provided to a processor of a general purpose computer, specialpurpose computer, or other programmable data processing apparatus toproduce a machine, such that the instructions, which execute via theprocessor of the computer or other programmable data processingapparatus, create means for implementing the functions/acts specified inthe flowchart and/or block diagram block or blocks.

These computer program instructions may also be stored in a computerreadable medium that can direct a computer, other programmable dataprocessing apparatus, or other devices to function in a particularmanner, such that the instructions stored in the computer readablemedium produce an article of manufacture including instructions whichimplement the function/act specified in the flowchart and/or blockdiagram block or blocks.

The computer program instructions may also be loaded onto a computer,other programmable data processing apparatus, or other devices to causea series of operational steps to be performed on the computer, otherprogrammable apparatus or other devices to produce a computerimplemented process such that the instructions which execute on thecomputer or other programmable apparatus provide processes forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof instructions, which comprises one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the block may occur out of theorder noted in the figures. For example, two blocks shown in successionmay, in fact, be executed substantially concurrently, or the blocks maysometimes be executed in the reverse order, depending upon thefunctionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts or carry out combinations of special purpose hardwareand computer instructions.

References in the claims to an element in the singular is not intendedto mean “one and only” unless explicitly so stated, but rather “one ormore.” All structural and functional equivalents to the elements of theabove-described exemplary embodiment that are currently known or latercome to be known to those of ordinary skill in the art are intended tobe encompassed by the present claims. No claim element herein is to beconstrued under the provisions of 35 U.S.C. section 112, sixthparagraph, unless the element is expressly recited using the phrase“means for” or “step for.”

The terminology used herein is for the purpose of describing particularembodiments only and is not intended to be limiting of the invention. Asused herein, the singular forms “a”, “an” and “the” are intended toinclude the plural forms as well, unless the context clearly indicatesotherwise. It will be further understood that the terms “comprises”and/or “comprising,” when used in this specification, specify thepresence of stated features, integers, steps, operations, elements,and/or components, but do not preclude the presence or addition of oneor more other features, integers, steps, operations, elements,components, and/or groups thereof.

The corresponding structures, materials, acts, and equivalents of allmeans or step plus function elements in the claims below are intended toinclude any structure, material, or act for performing the function incombination with other claimed elements as specifically claimed. Thedescription of the present invention has been presented for purposes ofillustration and description, but is not intended to be exhaustive orlimited to the invention in the form disclosed. Many modifications andvariations will be apparent to those of ordinary skill in the artwithout departing from the scope and spirit of the invention. Theembodiment was chosen and described in order to best explain theprinciples of the invention and the practical application, and to enableothers of ordinary skill in the art to understand the invention forvarious embodiments with various modifications as are suited to theparticular use contemplated.

What is claimed is:
 1. A method comprising: performing, by a processingthread, a process that analyzes transactional operations by maintainingthe transactional operations in transaction local side logs, and waitinguntil a successful transaction commit to append the transaction localside logs to a log stream, the processing thread processes thetransactional operations on a key used to determine whether existingdata is found for the key, wherein the transactional operations are spedup through parallelism based on partitioning tables across nodeshandling the transactional operations; performing a first process, by afirst processor, that processes updates for values of a key based onupdating a first start time table index using unique keys and a starttime field of a row for a first appearance of each unique key from thetransactional operations; and performing a second process, by a secondprocessor, that performs a deferred update by patching up of priorversions of the key for non-recent data upon determining that recentdata in the transactional operations is found for the key, wherein thenodes handling the transactional operations are based upon a subset of aprimary key.
 2. The method of claim 1, wherein the transactionaloperations are performed in a multi-master distributed computing system.3. The method of claim 2, wherein the process avoids information foruncommitted transaction changes, and the process that analyzestransactional operations is a grooming process.
 4. The method of claim3, wherein the transactional operations comprise update, delete andinsert operations, insert operations for new keys are handled as updatesthat specify values for a first version of a new key, delete operationsare handled as updates that change a value of the key to an indicatorthat indicates deletion, the first start time index is a globalin-memory index, and a table shard is assigned to the nodes handling thetransactional operations.
 5. The method of claim 4, wherein performingthe deferred update comprises: adding the first start time index usingthe unique keys and the start time field of the first appearance of eachunique key from the transactional operations; and looking up the firststart time index for an unknown value of an end time field of rows inthe non-recent data.
 6. The method of claim 5, wherein the end timefield of a row in the non-recent data is not assigned upon determiningthe key is not in the first start time index, the grooming process islimited to reading the log stream for avoiding information for theuncommitted transaction changes, and the end time field of a row in thenon-recent data is not assigned upon determining the key is not in thefirst start time index, and bitmap indexes are used to mark deletedrows.
 7. The method of claim 6, wherein the first start time index mapsthe key to the start time field of a row for the first appearance of thekey.
 8. The method of claim 6, further comprising: retiring rows fromaffected current files; outputting a history file per partition key;generating a new bit map for each affected current file, wherein the newbit map includes marking for the retired rows; initializing, a firstknown start time index; creating a current file and a history file foreach partition key group for a partition key; grouping all rows in apartition key group by primary key; for each primary key group: sortingrows by value in a begin time field of a row; writing of a first rowinto the first known start time index; for all rows except for a lastrow: writing values to a history file, wherein end time is assigned asrow_(i).EndTime=row_(i+1).BeginTime, where i is an integer indicatingposition of a row in a sorted order of a primary key group; and writingthe last row to the current file.
 9. A computer program product forprocessing updates for key values and for patch up of prior versions ofupdates and not yet patched updates, the computer program productcomprising a non-transitory computer readable storage medium havingprogram instructions embodied therewith, the program instructionsexecutable by a processor to cause the processor to: perform, by theprocessor, a process that analyzes transactional operations bymaintaining the transactional operations in transaction local side logs,and waiting until a successful transaction commit to append thetransaction local side logs to a log stream, the processing threadprocesses the transactional operations on a key used to determinewhether existing data is found for the key, wherein the transactionaloperations are sped up through parallelism based on partitioning tablesacross nodes handling the transactional operations; perform a firstprocess, by the processor, that processes updates for values of a keybased on updating a first start time table index using unique keys and astart time field of a row fora first appearance of each unique key fromthe transactional operations; and perform a second process, by theprocessor, that performs a deferred update by patching up of priorversions of the key for non-recent data upon determining that recentdata in the transactional operations is found for the key, wherein thenodes handling the transactional operations are based upon a subset of aprimary key.
 10. The computer program product of claim 9, wherein thetransactional operations are performed in a multi-master distributedcomputing system.
 11. The computer program product of claim 10, whereinthe process avoids information for uncommitted transaction changes, andthe process that analyzes transactional operations is a groomingprocess.
 12. The computer program product of claim 11, wherein thetransactional operations comprise update, delete and insert operations,insert operations for new keys are handled as updates that specifyvalues for a first version of a new key, delete operations are handledas updates that change a value of the key to an indicator that indicatesdeletion, the first start time index is a global in-memory index, and atable shard is assigned to the nodes handling the transactionaloperations.
 13. The computer program product of claim 12, whereinperforming the deferred update comprises: adding the first start timeindex using the unique keys and the start time field of the firstappearance of each unique key from the transactional operations; andlooking up the first start time index for an unknown value of an endtime field of rows in the non-recent data.
 14. The computer programproduct of claim 13, wherein the end time field of a row in thenon-recent data is not assigned upon determining the key is not in thefirst start time index, the grooming process is limited to reading thelog stream for avoiding information for the uncommitted transactionchanges, and the end time field of a row in the non-recent data is notassigned upon determining the key is not in the first start time index,bitmap indexes are used to mark deleted rows, and the first start timeindex maps the key to the start time field of a row for the firstappearance of the key.
 15. The computer program product of claim 14,further comprising program instructions executable by the processor tocause the processor to: retire, by the processor, rows from affectedcurrent files; output, by the processor, a history file per partitionkey; generate, by the processor, a new bit map for each affected currentfile, wherein the new bit map includes marking for the retired rows;initialize, by the processor, a first known start time index; create, bythe processor, a current file and a history file for each partition keygroup for a partition key; group, by the processor, all rows in apartition key group by primary key; for each primary key group: sort, bythe processor, rows by value in a begin time field of a row; write, bythe processor, of a first row into the first known start time index; forall rows except for a last row: write, by the processor, values to ahistory file, wherein end time is assigned asrow_(i).EndTime=row_(i+1).BeginTime, where i is an integer indicatingposition of a row in a sorted order of a primary key group; and write,by the processor, the last row to the current file.
 16. An apparatuscomprising: a memory configured to store instructions; and a processorconfigured to execute the instructions to: perform a process thatanalyzes transactional operations by maintaining the transactionaloperations in transaction local side logs, and waiting until asuccessful transaction commit to append the transaction local side logsto a log stream, the processing thread processes the transactionaloperations on a key used to determine whether existing data is found forthe key, wherein the transactional operations are sped up throughparallelism based on partitioning tables across nodes handling thetransactional operations; perform a first process that processes updatesfor values of a key based on updating a first start time table indexusing unique keys and a start time field of a row for a first appearanceof each unique key from the transactional operations; and perform asecond process that performs a deferred update by patching up of priorversions of the key for non-recent data upon determining that recentdata in the transactional operations is found for the key, wherein thenodes handling the transactional operations are based upon a subset of aprimary key.
 17. The apparatus of claim 16, wherein the transactionaloperations are performed in a multi-master distributed computing system.18. The apparatus of claim 17, wherein: the process avoids informationfor uncommitted transaction changes; the process that analyzestransactional operations is a grooming process; the transactionaloperations comprise update, delete and insert operations; insertoperations for new keys are handled as updates that specify values for afirst version of a new key; delete operations are handled as updatesthat change a value of the key to an indicator that indicates deletion;the first start time index is a global in-memory index; and a tableshard is assigned to the nodes handling the transactional operations.19. The apparatus of claim 18, wherein: performing the deferred updatecomprises: adding the first start time index using the unique keys andthe start time field of the first appearance of each unique key from thetransactional operations; and looking up the first start time index foran unknown value of an end time field of rows in the non-recent data;the end time field of a row in the non-recent data is not assigned upondetermining the key is not in the first start time index; the groomingprocess is limited to reading the log stream for avoiding informationfor the uncommitted transaction changes; the end time field of a row inthe non-recent data is not assigned upon determining the key is not inthe first start time index; bitmap indexes are used to mark deletedrows; and the first start time index maps the key to the start timefield of a row for the first appearance of the key.
 20. The apparatus ofclaim 19, wherein the processor is further configured to execute theinstructions to: retire rows from affected current files; output ahistory file per partition key; generate a new bit map for each affectedcurrent file, wherein the new bit map includes marking for the retiredrows; initialize a first known start time index; create a current fileand a history file for each partition key group for a partition key;group all rows in a partition key group by primary key; for each primarykey group: sort rows by value in a begin time field of a row; write of afirst row into the first known start time index; for all rows except fora last row: write values to a history file, wherein end time is assignedas row_(i).EndTime=row_(i+1).BeginTime, where i is an integer indicatingposition of a row in a sorted order of a primary key group; and writethe last row to the current file.